As junior recruiting approaches, we cannot help but speculate on the optimal way to compare apples to oranges – candidates across different fields (e.g. micro vs macro) and across universities. I speculated a while ago that a “best athlete” recruiting system across fields is prone to gaming. Each field might simply claim its candidate is great. To stop that happening, you might have to live with having slots allocated to fields and/or rotating slots over time.

It turns out that Yeon-Koo Che, Wouter Dessein and Navin Kartik have thought about something much more subtle along these lines in their paper “Pandering to Persuade“. They consider both comparisons across fields and across candidates from different universities. I’m going to give a rough synopsis of the paper.

Suppose the recruiting committee in an economics department is deciding whether to hire a theorist or a labor economist. There is only one labor economist candidate and her quality is known. There are two theorists, one from University A and one from University B. The recruiting committee would like to hire a theorist if and only if his quality is higher than the labor economist’s. Also, the recruiting committee and everyone else believes that, on average, candidates from University A are better than those from University B. But of course this is only true on average. Luckily some theorists can read the paper and help fine tune the committee’s assessment of the theory candidates. They share the committee’s interest in hiring the best theorist but they are quite shallow and hence uninterested in research outside their own field. In particular, theorists do not care for labor economics and always prefer a theorist at the end of the day.

So, the recruiting committee must listen to the theorists’ recommendation with care. First, the theorists have huge incentives to exaggerate the quality of their favored candidate if this carries influence with the committee. Hence, quality evaluations cannot be trusted. All the theorists can credibly do is say which candidate is better but not by how much. But there is a further problem: if the theorists say candidate B is better, given the committee’s prior, they might think better of candidate B and yet prefer to hire the labor economist! Being theorists, the sender(s) can do backward induction and they know the difficulty with their strategy if it is too honest. The solution is obvious to the theorists: extol the virtues of candidate A even when candidate B is a little better. Hence, in equilibrium, the candidate from the ex ante better university gets favored. But candidate B still has a shot: if they are sufficiently good, the theorists still recommend them. The committee may with some probability still go with the labor economist so it is risky to make this recommendation. But if candidate B is sufficiently good, the theorists may want to run this risk rather than push the favored candidate A. I refer you to the paper for the full equilibrium(a) but, as you can see, the paper is fun and interesting.

There are some extensions considered. In one, the authors study delegation to the theorists. Sometimes the department will lose out on a good labor economist but at least there is no incentive for the theorists to select the worst candidate. This is the giving slots to fields solution I wondered about and it is derived in this elegant model.

Glenn points out that the Hirsch index doesn’t do a great job at ranking economists. Nobel prize winner Roger Myerson’s Hirsch index is a mere 32. But he has a few papers with over a thousand citations. Seminal papers in economics tend to get a huge number of citations but most only get a few. So, the plain vanilla Hirsch index needs to be re-evaluated.

Glenn turns to the market to guide his measure. He studies an index of the form h is the highest number such that the author has at least h papers with at least a times h to the power b citations.The plain vanilla Hirsch index sets a=b=1. Glenn estimates a and b in various ways. In one method, he looks at the NRC department rankings and finds the variables a and b that best predict the NRC rank of a (young) economist’s department. To cut a long story short, a=5 and b=2 come out as the best predictors. With this estimation in hand, we can perform various comparisons – Which fields are highly cited? Which economists are highly cited? Etc..

Here are some tasty morsels of information. International finance, trade and behavioral economics are highly cited fields (Table 6). Micro theory and cross-sectional econometrics are the worst and IO does not do too well either. These facts mean Yale and NU, which are strong in these three areas, are under-cited economics departments. But basically one gets the picture that an economists citations are closely connected to the rank of the university where s/he is employed.

Ranking young economists, it is pretty obvious who is going to come out on top: Daron Acemoglu with an index of 7.84 (Table 7). This means Daron has 7.84 papers with roughly 300 citations. Ed Glaeser and Chad Jones are close behind. Once you adjust by field, more theorists start to rank highly: Glenn, Ilya Segal, Stephen Morris and Susan Athey pop up. Also, my friend Aviv Nevo gets a shout out as an underplaced guy.

A few comments:

Most of these people are tenured well before their citations go crazy. Expert opinion not data-mining leads to their tenure. This tells you how well expert opinion predicts citations. Also, to the extent that citations take time, expert opinion will always play a role in tenure decisions. There is a difference between external opinion and internal opinion. The same few people always get asked to write letters and they will do a good job. But internal opinions may be more noisy and depend on the quality of the department. Then, Glenn’s field-adjusted citation measure gives you some idea of a candidate’s quality and might be a valuable input into the tenure decision.

Finally, there are citations and citations. A paper getting regular cites in top journals is better than a paper getting cites in lower tier journals. This can be dealt with by improving the citation index.

At another extreme, some papers may be journalistic, not academic, and then their citations mean less. For example, Malcom Gladwell gets high citations for the Tipping Point but he did not do any of the original scientific research on which his book is based. Of course he writes wonderfully and comes up with amazing examples and he is clearly an intellectual. I bet Harvard would love to have him an as an adjunct professor but they will not give him a tenured professorship.

Despite these caveats, the generalized Hirsch index is an interesting input for academic decision-making.

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For 15 years, the British bookmaker William Hill allowed bettors to wager on their own weight loss, often taking out full-page newspaper ads to publicize the bet. This was a clear opportunity for those looking to lose weight to make a commitment, with real teeth. Here is a paper by Nicholas Burger and John Lynham which analyzes the data.

Descriptive statistics are presented in Table 2, which shows that 80% of bettors lose their bets. Odds for the bets range from 5:1 to 50:1 and potential payoffs average $2332.9 The average daily weight loss that a bettor must achieve to win their bet is 0.39 lbs. In terms of reducing caloric intake to lose weight, this is equivalent to reducing daily consumption by two Starbucks hot chocolates. The first insight we draw from this market is that although bettors are aware of their need for commitment mechanisms, those in our sample are not particularly skilled at selecting the right mechanisms.10 Bettors go to great lengths to construct elaborate constraints on their behaviour, which are usually unsuccessful.

Women do much worse than men. Bets in which the winnings were committed to charity outperformed the average. Bets with a longer duration (Lose 2x pounds in 2T days rather than x pounds in T days) have longer odds, suggesting that the market understands time inconsistency.

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Everyone is jumping on the bandwagon, including Tyler Cowen, Greg Mankiw, and even Sandeep. They are all trumpeting this study whose bottom line is that student evaluations of teachers are inversely related to the teacher’s long-run added value. The conclusion is based on two findings. First, if my students do unusually well in my class they are likely to do badly in their followup classes. Second, if my students evaluate me highly it is likely that they did unusually well in my class.

I am not jumping on the bandwagon. I have read through the paper and while I certainly may have overlooked something (and please correct me if I have) I don’t see any way the authors have ruled out the following equally plausible explanation for the statistical findings. First, students are targeting a GPA. If I am an outstanding teacher and they do unusually well in my class they don’t need to spend as much effort in their next class as those who had lousy teachers, did poorly this time around, and have some catching up to do next time. Second, students recognize when they are being taught by an outstanding teacher and they give him good evaluations.

The authors of the cited study are every time quick to jump to the following conclusion: older, experienced teachers, and especially those with PhD’s know how to teach “lasting knowledge” whereas younger teachers “teach to the test.” That’s a hypothesis that sounds just right to all of us older, experienced teachers with PhD’s. But is it any more plausible than older experienced teachers with tenure don’t care about teaching and as a result their students do poorly? Not to me.

Dear 310-2 students who will be filling out evaluations this week: please don’t hold it against me that I am old, experienced, and have a PhD.

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Long before behavioral economics had a name, marketers were using it. “Three for the price of two” offers and extended-payment layaway plans became widespread because they worked—not because marketers had run scientific studies showing that people prefer a supposedly free incentive to an equivalent price discount or that people often behave irrationally when thinking about future consequences. Yet despite marketing’s inadvertent leadership in using principles of behavioral economics, few companies use them in a systematic way. In this article, we highlight four practical techniques that should be part of every marketer’s tool kit.

Among the key points, the one that stands out is “Make a product’s price less painful.” This includes profiting from hyperbolic discounting and exploiting mental accounting. Manipulating default options and harnessing choice-set-dependent preferences also figure prominently.

Evidently marketing will soon supplant finance as the relevant outside option for new Economics PhD’s bargaining over academic salaries.

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Is it a superstition that babies born in a Year of the Dragon will have good luck? The Taiwanese government wanted to dispell the superstition.

The demographic spike in 1976 was sufficiently large that governments decided to issue warnings in 1987 against having babies in Dragon years because of the problems they caused for the educational system, particularly with respect to finding teachers and classroom space. Editorials were issued that claimed no special luck or intelligence for Dragon babies and a government program in Taiwan was designed to alert parents to the special problems faced by children born in an unusually large cohort (Goodkind, 1991, p. 677 cites multiple newspaper accounts of this).

But the effort failed and another spike was seen in 1988. Why? Because the dragon superstition is true. In this paper by Johnson and Nye, among Asian immigrants to the US, those born in Dragon years are compared to those born in non-Dragon years. Dragon babies are more successful as measured in terms of educational attainment. And the difference is larger than the corresponding difference for other US residents.

And of course it turns out that this is due to the self-fulfilling nature of the superstition. Asian Dragon babies have parents who are more successful and they are more likely to have altered their fertility timing in order to have a baby in a Dragon year. Is this because the smarter parents were more likely to be dumb enough to believe the superstition?

Or is it because of statistical discrimination? Since the Dragon superstition is true, being a Dragon is a signal of talent and luck. Unless these traits are observable without error, even unlucky and untalented Dragons will be treated preferentially relative to unlucky and untalented non-Dragons. Smart parents know this and wait until Dragon years.

Thanks to Toomas Hinnosaar for the pointer.

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About a year ago I posted a link to a YouTube video of the Golden Balls “Split or Steal” game, hailing it as a godsend for teachers of game theory and the Prisoners’ Dilemma. That video has made its way around the web in the year since and I sat down to prepare my introductory game theory lecture yesterday looking for something new.

Well, it turns out that now there are many, many new videos of Split or Steal on YouTube and you can spend hours watching these. Here is my favorite and the one I used in class today.

MBA students pay high fees, leave the job market for two years and lose income and face the stress of getting a job when they’re done. Why?

The value added from an MBA must be high. Where does it come from? The teaching, the professors, the exams and grades. All that value has to be substantial. But undoubtedly, another huge part of the value comes from meeting other like-minded, smart, beautiful, go-getting people.

But the value of networking can be generated without a bricks-and-mortals B School. At least this is the bet taken by a budding education entrepreneur, Anton Napolitanokich, based in Moscow.

“Leading B Schools in the US and Europe are not going to risk their reputation by going digital,” said Napolitanokich. “And nor are great students in those regions going to give up the brand reputation that a HBS degree gives you to do something risky. But here in Moscow, there is little competition and a more amenable market. The Virtual MBA is the future of business education”

Napolitanokich’s business model is based on social networking websites like Facebook and as well pure, old-fashioned “networking” in nightclubs! “MBA students are in constant wireless contact already. All they need is someone to screen the group they interact with. That’s the key to what the traditional bricks and mortar B Schools do and we will replicate that. Of course we are total unknowns right now. So, we will do an excellent job letting in great students in our first round. We will let them in for free to prime the pump. If it works out, everyone will want to interact with our star students. In the next rounds, we will auction off entry into this select group It is kind of like a nightclub: you let in the good-looking people for free and then wait for everyone else to line up to get in. Of course, we can’t let in everyone – we have to maintain a high quality pool. So, we’ll restrict the number of spots and let the bidding takeoff! If it works, the price will be even higher than a traditional MBA! Go to www.virtualmba.com and apply for admission right away! It’s the future – even Sergey Brin is interested in the idea. He’s from Moscow you know. Brin ses we are the new Amazon and they are the old Barnes and Noble”

But what will the students actually be doing? Napolitanokich envisages that students will play interactive business games. The point of the games is more to get the students to get to know each other, establish networks and friendships. In a business coup, Napolitanokich has partnered with Disney to produce interactive business games. Disney’s Club Penguin website has been a huge hit with the elementary school set. Kids get to choose an avatar in penguin form to play interactive video games and hang out with other avatar penguins in chat rooms. Napolitanokich envisages a similar scenario for the b school games. Preppy J Crew wearing MBA avatars will engage in strategic competition, negotiation and marketing and have time to relax in virtual bars and restaurants. Disney finds the model every promising and hopes to create connecting sites all the way from Club Penguin up the age ladder to Virtual MBA, training budding entrepreneurs in high school.

Of course, only so much can be achieved by networking remotely. Actual face-to-face communication is vital too. Napolitanokich envisages intense live-in weeks where flocks of virtual MBAs fly in to isolated resort locations for intense interactive teaching sessions. So, some professors are inescapable he admits. But they will be a new breed of hyper-profs, flying in and out for short trips, living everywhere and nowhere. Ciphers who facilitate and coordinate student-student interaction but otherwise get out of the way. The still young century welcomes a new model for education.

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I heard this from Marco who heard it from Tzachi. Not sure what to make of it, but that will not deter me from ruminating publicly

There is a sack of chocolate and you have two options: either take one piece from the sack to yourself, or take three pieces which will be given to Dylan. Dylan also has two options: one pieces for himself or three to you. After you both made your choices independently each goes home with the amount of chocolate he collected.

My friend Jamie is a professional poker player, and he came across a great example along the lines of the Prisoner’s Dilemma.

Here is what he reports:

I played a poker tournament at Caesar’s Palace last night with the
following setup: The buy-in is $65, which gets you 2500 chips. There
is also the option to buy an additional 500 chips for $5 more, giving
you a total of 3000 chips for $70. At 1 cent/chip, this add-on sounds
like a great bargain compared to the 2.6 cents/chip of the regular
buy-in.

The kicker is that the house keeps the entire $5 add-on fee; none of
it goes into the prize pool.

Each of these is equivalent to a Prisoners’ Dilemma. That should be obvious in the first case. In the second case, notice that if you buy the additional chips you deflate the value of the others’ chips. (Poker seignorage!) If you were to present either of these examples to students, I would bet that most of them would play the corresponding Defect strategy. And this would make for a great teaching device if you show it to them before teaching the Prisoners’ dilemma. Because the usual framing of the prisoner’s dilemma suggests to students that they ought to be cooperative. This is the main reason students are often confused by the Prisoners’ dilemma.

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Kjerstin Erickson is selling a 6% stake in her lifetime income for $600,000 through a vehicle known as the Thrust Fund:

Erickson’s Thrust Fund comes at a time of deep experimentation in early-stage financing across the technology and media industries. The transparency afforded by social networking is making it easier for investors to vet people’s reputations and hold them accountable. At the same time, the initial amount of capital needed to build, market and distribute a product or service has fallen, undermining the venture capital model and making angel investors relatively more powerful.

Think of Kjerstin as a self-managed firm. She could issue debt or equity. The Modigliani-Miller theorem explains why most people in Kjerstin’s position choose to issue debt. Her income is taxed, but interest on debt is often tax-deductible.

But a key difference between Kjerstin and a firm is that you if you acquire Kjerstin you cannot fire the manager. So your capital structure is also your managerial incentive scheme. Debt makes Kjerstin a risk-lover: she gets all the upside after paying off her debts and her downside is limited because she can just default. With equity she owns 94% of her earnings no matter what they are.

So many questions come up, here are just a few.

Why don’t we replace student loans with student shares? Arguably the reason we stick with debt is that it is good policy to induce risk-taking. Because the large numbers means that aggregate risk is small and society benefits more from the big hits than it loses from the misses.

Do Kjerstin’s investors get voting rights?

Does the contract give her the freedom to issue more shares in the future? She wants this option but her investors don’t. The more shares she sells the less incentive she has to work hard.

Kjerstin now has a huge incentive to take in-kind compensation that is hard to value. In corporate finance, this is called diverting the cash flows. How does her contract deal with that?

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The primary rationale for tenure is academic freedom. A researcher may want to pursue an agenda which is revolutionary or offensive to Deans, students, colleagues, the public at large etc. However, the agenda may be valuable and in the end dramatically add to the stock of knowledge. The paradigmic example is Galileo who was persecuted for his theory that the Sun is at the center of our planetary system and not the Earth. Galileo spent the end of his life under house arrest. Einstein considered Galileo the father of modern science. Tenure would now grant Galileo the freedom to pursue his ideas without threat of persecution.

From the profound to the more prosaic: the economic approach to tenure. For economists, tenure is simply another contract or institution and we may ask, when is tenure the optimal contract? My favorite answer to this question is given by Lorne Carmichael’s “Incentives in Academics: Why Is There Tenure?” Journal of Political Economy (1996).

Suppose a university is a research university that maximizes the total quality of research. Let’s compare it to a basketball team that wants to maximize the number of wins. Universities want to hire top researchers and basketball teams want to hire great players. Universities use tenure as their optimal contract but basketball teams do not. Why the difference?

On the basketball side of things it’s pretty obvious. Statistics can help to reveal the quality of a player and you can use the data to distinguish a good player from a bad player. And this can inform your hiring and retention decisions.

On the research side, things are more complicated. Statistics are harder to come by and interpret. On Amazon, Britney Spears’ “The Singles Collection” is #923 in Music while Glenn Gould’s “A State of Wonder: the Complete Goldberg Variations” is #3417. Even if we go down to subcategories, Britney is #11 in Teen Pop and Glenn is #56 in Classical.

So, is Britney’s stuff better than Bach, as interpreted by Glenn Gould? I love “Oops..I did it Again”, but I am forced to admit that others may find Britney’s work to be facile while there is timeless depth to Bach that Britney can’t match.

I’ve tried to offer an example which is fun, but it is also a bit misleading as the analogy with scientific research is flawed. First, music is for everyone, while scientific research is specialized. Second, there is an experimental method in science so it is not purely subjective. But the main point is there is a subjective component to evaluating research and hence job candidates in science. There is less of this in basketball. Shaq is less elegant than Jordan but he gets the job done nonetheless. The subjective component actually matters a lot in science because of the specialization. Scientists are better placed to determine if an experiment or theory in their field is incorrect, original or important. And they are better placed to make hiring decisions, when even noisy signals of publications and citations are not available.

Subjective evaluation is the starting point of Carmichael’s model of tenure. If you are stuck with subjective evaluation, the people who know a hiring candidate’s quality best are people in the department that is hiring him. If the evaluators are not tenured, they will compete with the new employee in the future. If the evaluators hire who is higher quality than they are themselves, they are more likely to get sacked than the person they hire. In fact, the evaluators have the incentive to hire bad researchers so they are secure in their job. This reduces the quality of research coming out of the university. On the other hand, if the evaluator is tenured, their job is secure and this increases their incentive to be honest about candidate quality and leads to better hiring. If there are objective signals as in sport, there is less need for subjective evaluation and hence no need for tenure.

This is the crux of the idea. It is patronizing for anyone to impose their tastes of Britney vs Bach on others. Everyone’s opinion is equally valid. It is possible to say Scottie Pippin was a worse basketball player than Jordan – the data prove it. Science is somewhere in between. There is both an objective component and a subjective component. We then have to rely on experts. Then, the experts may have to be tenured.

This Friday (12th February) is Valentine’s Day. Now before you say, “oh no it isn’t!” I have to beg to differ. That is the day our two youngest children are, near as I can tell, compelled to bring a Valentine’s card to every other person in the class. The school sent home a convenient list of the some 45 names in total that require cards and the instruction that they be prepared for Friday. And by prepared, you can’t just go to the store, buy a pack and put names on it. Nor can you, as I had wanted to do, draw a card on the computer and hit print (quantity = 45). Each requires individual attention. Suffice it to say, this is an exercise requiring many hours and, frankly, if we didn’t have a snow day today (that is, a day whereupon fear of snow = no school for you), it is unclear whether the household could produce the required amount of love.

And of course the parents wind up doing most of the work. I would suggest however that schools will push parents to their limits in terms of busy work whether or not that includes making Valentines. That is, if the Valentine exchange were banned it would only be replaced by some other after-school craft or chore.

What’s surprising is that Valentines has survived this long in US schools. It’s too focal and so too easy for parents to coordinate their outrage against. Whereas yet another assignment to look up native american tribes on the internet just blends in with all the rest.

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I’ve previously discussed the thorny issue of the overzealous advocacy of a traditional recipe to the exclusion of all others. In response to Florence Fabricant’s claim, for instance, that “for any pasta all’amatriciana to be authentic, it must be made with guanciale (pork jowl),” not bacon or pancetta, I responded that “too many food writers construct a counterfactual Italy of culinary dogmatism, a population of finger-wagging guanciale zealots, a nation…harrumphing around about how the world is going to shit now that people are making amatriciana with pancetta…People and recipes aren’t anthropological tokens. They’re living things, the products of neural assemblies and proteins and chemicals bouncing across the ages. Narrow your gaze and squint your eyes too tightly in the search for authenticity, and you might miss that whole, beautiful landscape.”

Perhaps I should revise this statement: clearly, there are some finger-wagging guanciale zealots in Italy. They tend to gravitate, it seems, toward the Ministry of Agriculture. The question of whether “zero tolerance,” when it comes to food, is fascist, patronizing, noble—or all three—is certainly one for further contemplation.

Wine produced around Montalcino can be called Brunello di Montalcino only if it is 100% Sangiovese. If imposters put Cabernet into their Brunello, and people like it, should the rules of the appelation be vigorously enforced? You are inclined to say no because people should have what they like. But if it were that simple there would be no reason for the appelation at all.

It could be that people want to know for sure which wine is 100% Sangiovese (and meets other benchmarks) and which is/does not. The appelation system allows them to know that without preventing them from having their SuperTuscan Cab/Sanjo blends if they prefer that.

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In principle a prediction market should generate more accurate predictions than a simple poll. For example, in an election, the outcome of a poll should be known to the traders and incorporated into their trades. But in practice, the advantage of prediction markets is small, or so suggests a new study.

In a new study, Daniel Reeves, Duncan Watts, Dave Pennock and I compare the performance of prediction markets to conventional means of forecasting, namely polls and statistical models. Examining thousands of sporting and movie events, we find that the relative advantage of prediction markets is remarkably small. For example, the Las Vegas market for professional football is only 3% more accurate in predicting final game scores than a simple, three parameter statistical model, and the market is only 1% better than a poll of football enthusiasts.

More here. My view is that there is no theoretical reason for interpreting a market price in a prediction market as a probability. That is, if Coakley is trading at 75 cents there is no reason to interpret that as a 75 percent probability that Coakley will win. At best there is an ordinal relationship: a higher price means a higher probability. Likewise with a poll.

Studies like these should instead be measuring the conditional probability of an event given the price observed in the market. Because, even an “innacurate” prediction can be a very good one. To take an extreme case the market might always underprice the probability of a Coakley win by 25%. But then by dividing the market price by .75 we can infer the right probability with perfect accuracy.

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I have a student who is in charge of Northwestern’s Undergraduate Economics Society and he is planning an event in the Spring. They have some money and they want to organize an activity for their membership that will be fun and economics-oriented. Think of this as an opportunity to design an experiment involving any number of students (up to hundreds of students), but it should be fun as well as educational. I know that our readers will have some good ideas for them. Please share them in the comments.

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Via The Sports Economist comes a report that Las Vegas bookmakers are seeing big losses on NFL games this year owing to the large number of very bad teams and the difficulty of getting the point spreads right.

The Golden Nugget sports book, for instance, opened with St. Louis getting 12.5 points (the half to help with ties). That way, if you bet the Rams and the actual game ended 21-10 Indy, you’d win the bet with a score of 22.5-21 St. Louis.

A betting line is fluid though and will correct itself as money pours in for the favorite or underdog. Despite the Rams getting all those points, at home no less, the money kept going to Indy. The line reacted by moving all the way to 14 points at kickoff.

Still 90% of the money was on the Colts at game time and the Colts won 42-6. Perhaps the problem is that there is a large variance in the market’s estimate of the likely point spread. The bookmaker has to make a good guess the first time becuase too much adjustment of the line allows arbitrage. And a bad guess can be costly.

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Its easy to make up just-so stories to explain differences across siblings as being caused by birth-order. This article casts doubt on the significance of birth order.

But we can ask the question of whether birth order should matter and in what ways. Should natural selection imply systematic differences between older and younger siblings? Here is one argument that it should. Siblings “share genes” and as a consequence siblings have an evolutionary incentive to help each other. Birth order creates an asymmetry in the ways that different siblings can help each other. In particular, oldest siblings learn things first. They are the first to experiment with different survival strategies. The results of these experiments benefit all of the younger siblings. (Am I a good hunter? If so, my siblings are likely to be good hunters too.) Younger siblings have less to offer their older siblings on this dimension.

As a result we should expect older siblings to be more experimental than their younger siblings and more experimental than only children.

Here is evidence that older siblings have more years of education than younger siblings and more years of education than only children.

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The link I posted previously was somewhat outdated as it mentioned only that furloughs were under consideration. As a part of the recent budget agreement, the UC furlough is now a done deal. Hereare some more recent stories.

I have heard that, system-wide, professors will take an 8% cut in pay. The word “furlough” usually means something like a temporary layoff. Here it means that workers will have shorter hours and commensurately lower pay. For example, UC non-faculty staff will have a few days off each month.

What are the marginal hours where Professors will be furloughed? Saturdays. That is, no classes will be cut, all administrative duties remain intact, pay is cut 8%. Presumably this means that my colleagues in UC system will be doing 8% more surfing the web when they are not in the classroom.

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In the last lecture we demonstrated that there was no way to efficiently provide public goods, whether via a market or any other institution. Now we turn to private goods.

We start with a very simple example: bilateral trade. A seller holds an object that is valued by a potential buyer. We want to know how to bring about efficient trade: the seller sells the object to the buyer if, and only if, the buyer’s willingness to pay exceeds the seller’s.

We first analyze the problem using the Vickrey-Clarke-Groves Mechanism. We see that the VCG mechanism, while efficient, is not feasible because it would require a payment scheme which results in a deficit: the buyer pays less than the seller should receive.

Then, following the lines of the public goods problem from the previous lecture we show that in fact there is no mechanism for efficient trade. This is the dominant strategy version of the Myerson-Satterthwaite theorem. In fact, we show that the best mechanism among all dominant-strategy incentive compatible and budget balanced mechanisms (i.e. the second-best mechanism) takes a very simple form. There is a price fixed in advance and the buyer and seller simply announce whether they are willing to trade at that price.

We see the first emergence of something like a market as the solution to the optimal design of a trading institution. We also see that markets are not automatically efficient even when there are no externalities, and goods are private. There is a basic friction due to information and incentives that constrains the market.

Next we consider the effects of competition. Our instincts tell us that if there are more buyers and more sellers, the inefficiency will be reduced. By a series of arguments I show the first sense in which this is true. There exists a mechanism which effectively makes sellers compete with one another to sell and buyers compete with one another to buy. And this mechanism improves upon the fixed price mechanism because it enables the traders themselves to determine the most efficient price. I call this the price discovery mechanism (it is really just a double auction.)

Finally, in one of the best moments of the class, what was previously some random plots of values and costs on the screen coalescees into supply and demand curves and we see how this price discovery mechanism is just another way of seeing a competitive market. This is the second look at how markets emerge from an analytical framework that did not presuppose the existence of markets at the beginning.

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This week, many of my former students will be undergoing the painful experience of taking the Virginia bar exam. My general view on bar exams is that they should be abolished, or at least that you should not be required to pass one in order to practice law. If passing the exam really is an indication of superior or at least adequate legal skills, then clients will choose to hire lawyers who have passed the exam even if passage isn’t required to be a member of the bar. Even if a mandatory bar exam really is necessary, it certainly should not be administered by state bar associations, which have an obvious interest in reducing the number of people who are allowed to join the profession, so as to minimize competition for their existing members.

What changes would we see if it was no longer necessary to pass the bar in order to practice law? We can analyze this in two steps. First, hold everything else about the bar exam fixed and ask how the market will react to making it voluntary.

The first effect would be to encourage more entry into the profession. Going to law school is not as much of a risk if you know that failing the bar is not fatal. There would be massive entry into specialized law education. Rather than go to a full-fledged law school, many would take a few practical courses focused on a few services. Traditional law schools would respond by becoming even more academic and removed from practice.

Eventually the bar will be taken only by high-level lawyers who work in novel areas and whose services require more creativity and less paper pushing. But the bar will no longer be the binding entry barrier to these areas. The economic rationale for the entry barrier is to create rents for practicing lawyers so that they have something to lose. This keeps them honest and makes their clients trust them.

Now reputation will provide these rents. Law firms, even moreso than now, will consist of a few generalist partners who embody all of the reputation of the firm and then an army of worker-attorneys. All of the rents will go to the partners. The current path of associate-promoted-to-partner will be restricted to only a very small number of elites.

As a result of all this, competition actually decreases at the high end.

All of these changes will alter the economics of the bar exam itself. Since the bar is no longer the binding entry barrier, bar associations become essentially for-profit certification intermediaries. This pushes them either in the direction of becoming more selective, extracting from further increases in rents at the high end or less selective and becoming effectively a driver’s license that everyone passes (and pays a nominal fee.) Which direction is optimal depends on elasticities. Probably they will offer separate high-end and low-end exams.

My bottom line is that banning the bar increases welfare but perhaps for different reasons than Somin has in mind. Routine services will become more competitive and this is good. Increased concentration at the high end is probably also good because market power means less output and for the kinds of lawyering they do, reduced output is welfare-improving.

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This is not one of those arrangements where donors can sponsor a needy child or a sorghum farmer in the developing world. The person asking for help is a 21-year-old neurobiology major at Harvard, and she is requesting a loan from Harvard alumni.

The service, Unithrive, resembles micro-lending in a number of ways (except perhaps the sticker.)

Unithrive, which made its debut last month, matches alumni lenders and cash-strapped students, who post photographs and biographical information and can request up to $2,000. The loans are interest-free and payable within five years of graduation.

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We used to be in denial that there were any bubbles, now everything is a bubble. This article in the Chronicle of Higher Education sounds the alarm on higher education (tassle twirl: lone gunman.)

Is it possible that higher education might be the next bubble to burst? Some early warnings suggest that it could be.

With tuitions, fees, and room and board at dozens of colleges now reaching $50,000 a year, the ability to sustain private higher education for all but the very well-heeled is questionable. According to the National Center for Public Policy and Higher Education, over the past 25 years, average college tuition and fees have risen by 440 percent — more than four times the rate of inflation and almost twice the rate of medical care. Patrick M. Callan, the center’s president, has warned that low-income students will find college unaffordable.

Meanwhile, the middle class, which has paid for higher education in the past mainly by taking out loans, may now be precluded from doing so as the private student-loan market has all but dried up.

The analogy to the housing bubble is certainly tempting. Pell grants and Stafford Loans are to Colleges what Fannie and Freddie are to housing. It is undeniable that easy access to credit fueled rises in tuition. It is not a stretch to think of these loan programs as essentially subsidies to Universities as they raise tuition dollar for every dollar of loans that are essentially forgiven.

But the analogy doesn’t go any farther than that. There is no speculation fueling demand for higher education. There is a permanent and measurable difference in earnings for college graduates. There will continue to be a robust market for credit to students because, to borrow a phrase, consumption wants to be smoothed. And unlike subsidized loans for housing, there is a real externality that justifies continued federal presence in the student loan market.

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Greg Mankiw thinks B-School economists are “practical” and “empirical” while Econ Dept economists are free to be abstract and theoretical.

I don’t think this is true for the research done by economists differs across these two types of schools but it is true that the teaching is different. The MEDS Dept at Kellogg where I work is somewhat different from other business schools as it has always been very theory focused. The Econ group at Stanford GSB is similar. Some of the best work in game theory, contract theory and decision theory came out of these departments.

It is the case, as Mankiw says, that teaching has to be practical and useful in a B School. Whether that drives research or not depends on the philosophy of the school. I have never felt any pressure for my research to be practical.

Mankiw writes his post to answer David Brooks’s query about why B School economists are giving him better answers about the current state of the economy. As finance is a B School specialty, it very natural that B schools profs may know more about what a CDS is without having to look it up on Wikipedia! But again, finance economists are not more “practical” or “empirical” than econ dept economists. I bet Doug Diamond and Milt Harris at Chicago GSB have really perceptive things to say about the financial crisis as has Oliver Hart at Harvard Econ. They will use simple, clear models (hopefully!), to explain their ideas about how to fix incentives in the financial sector. And then maybe somone will give a little theory a chance as much as data analysis!

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Here is an interesting article about the history of the Ivy league and the member Universities’ attitudes toward sport.

The Ivy is never going to be the Southeastern Conference—and nobody is suggesting it should be. The schools don’t need the exposure of sports to attract students and alumni donations. But some of the league’s alumni complain that the schools offer their students the best of everything, except in this one area. “Why not give them the same opportunities and the same platform in athletics that you do in academics?” says Marcellus Wiley, a former NFL defensive end who played at Columbia in the 1990s. “I think they should revisit everything.”

If we take the objective to be maintaining reputation and attracting donations then there is a broader question. Why is the concentration among schools which compete on academic excellence so much higher than among those that compete on athletics? Competition for dominance in sport appears to be more costly and occurs at a higher frequency that the competition for academic excellence. Some possible reasons:

There is more variance in academic talent than in talent in sports. Thus the top end is thinner and the market is smaller.

There is more continuity in academic strength purely because of numbers. A bad recruiting class for the basketball team a few years in a row and you are back to square one. A freshman class at Harvard is large enough that variations wash out.

It is easier to throw money at sport. One coach makes the whole program. Assessing the talent of faculty and attracting it with money is more complicated. And maybe irrelevant.

I would like to believe 1 but I don’t. I would like not to believe 3 but its hard. I do believe 2.

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A post at Language Log explores the use of mathematics in linguistics. It closes with

Anyhow, my conclusion is that anyone interested in the rational investigation of language ought to learn at least a certain minimum amount of mathematics.

Unfortunately, the current mathematical curriculum (at least in American colleges and universities) is not very helpful in accomplishing this — and in this respect everyone else is just as badly served as linguists are — because it mostly teaches thing that people don’t really need to know, like calculus, while leaving out almost all of the things that they will really be able to use. (In this respect, the role of college calculus seems to me rather like the role of Latin and Greek in 19th-century education: it’s almost entirely useless to most of the students who are forced to learn it, and its main function is as a social and intellectual gatekeeper, passing through just those students who are willing and able to learn to perform a prescribed set of complex and meaningless rituals.)

Before getting into economics and after getting out of physics, I took calculus and found it very useful and interesting for its own sake. I do see that the way calculus is taught in the US is geared toward engineers and physicists, but I have a hard time thinking of what mathematics would substitute for calculus in the undergraduate curriculum if the goal was to teach students something useful. It can’t be analysis or topology. I took abstract algebra as an undergraduate and found it esoteric and boring. Discrete mathematics? OK maybe statistics, but don’t you need integration for that? Help me out here, if you had the choice, what would you replace calculus with? And remember the goal is to teach something useful.

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I got two speeding tickets in less than one year. I worked off the first one by taking an online course. For the second one, they make you go to an 8 hours (!) course over two nights. The only course that fit my schedule was in Rolling Meadows. Just like Old Orchard in Skokie, there may have been farmland there a while ago but there are no rolling meadows now.

It’s obvious that the punishment in terms of wasted time is harsh so that you do not speed again. Your first thought is whether you can persuade the teacher to let you go early. This desire was very strong on Thursday night when the Bulls were playing the Celtics in Game 6 of their best of seven series. The class took place in the basement of a courthouse and it turns out the police monitor the teacher to make sure he does not let the class off early. Of course the teacher would love to go home early too so the incentives for renegotiation are huge. The police have to stay anyway so they enforce the rules.

So I was stuck in the class but I kind of enjoyed it because I got to meet people I do not meet everyday otherwise. I also got lots of information that I would not gotten in my normal interactions.

The hippie woman: “I got a ticket because I gave a ride to a Jamaican guy who turned to be a homeless ex-convict. I got a speeding ticket when I got scared driving him to his shelter.”

The hippie girl: “When I have fatigue, I do yoga to wake up before I drive”

The truck driver: “Go to White Castle before you drink. The grease soaks up the beer.”

The Comcast guy: “Ritalin is like cocaine if you don’t have ADD. I’m taking Ritalin now so I can sit in this class without going crazy.”

Lucca, the waiter: “The strip clubs in Indiana are better than the strip clubs in Chicago. The Indiana girls are nicer and they want dates. Always go to a ranch style strip club.”

I’m not sure how the last comment was related to the class.

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The NBA will not draft players who are under 19 or who are not at least one year past high school graduation. Most players opt for at least one year of NCAA basketball where they are unpaid and (at least nominally) full-time students. The first step toward the unraveling of this system has occurred as Jeremy Tyler has left San Diego High School and will skip his senior year to play professional basketball in Europe. After two years he will be eligible for the NBA draft at which point he is a likely number 1 pick.

“It’s significant because it shows the curiosity for the American player just refusing to accept what he’s told he has to do,” Vaccaro said. “We’re getting closer to the European reality of a professional at a young age. Basically, Jeremy Tyler is saying, ‘Why do I have to go to high school?’ ”